User profiles for K. M. Naegle
Kristen M. NaegleUniversity of Virginia Verified email at virginia.edu Cited by 1156 |
Avoiding common pitfalls when clustering biological data
Clustering is an unsupervised learning method, which groups data points based on similarity,
and is used to reveal the underlying structure of data. This computational approach is …
and is used to reveal the underlying structure of data. This computational approach is …
[HTML][HTML] Injury-induced HDAC5 nuclear export is essential for axon regeneration
Reactivation of a silent transcriptional program is a critical step in successful axon
regeneration following injury. Yet how such a program is unlocked after injury remains largely …
regeneration following injury. Yet how such a program is unlocked after injury remains largely …
[PDF][PDF] A path to translation: How 3D patient tumor avatars enable next generation precision oncology
3D patient tumor avatars (3D-PTAs) hold promise for next-generation precision medicine.
Here, we describe the benefits and challenges of 3D-PTA technologies and necessary future …
Here, we describe the benefits and challenges of 3D-PTA technologies and necessary future …
Phosphoproteomics of collagen receptor networks reveals SHP-2 phosphorylation downstream of wild-type DDR2 and its lung cancer mutants
…, S Gridley, B Leitinger, KM Naegle… - Biochemical …, 2013 - portlandpress.com
Collagen is an important extracellular matrix component that directs many fundamental
cellular processes including differentiation, proliferation and motility. The signalling networks …
cellular processes including differentiation, proliferation and motility. The signalling networks …
Predicting patient response to the antiarrhythmic mexiletine based on genetic variation: personalized medicine for long QT syndrome
Rationale: Mutations in the SCN5A gene, encoding the α subunit of the Nav1.5 channel, cause
a life-threatening form of cardiac arrhythmia, long QT syndrome type 3 (LQT3). Mexiletine…
a life-threatening form of cardiac arrhythmia, long QT syndrome type 3 (LQT3). Mexiletine…
[HTML][HTML] Different Epidermal Growth Factor Receptor (EGFR) Agonists Produce Unique Signatures for the Recruitment of Downstream Signaling Proteins*♦
…, L Huelsmann, NJ Bessman, KM Naegle… - Journal of Biological …, 2016 - ASBMB
The EGF receptor can bind seven different agonist ligands. Although each agonist appears
to stimulate the same suite of downstream signaling proteins, different agonists are capable …
to stimulate the same suite of downstream signaling proteins, different agonists are capable …
ProteomeScout: a repository and analysis resource for post-translational modifications and proteins
…, AS Holehouse, KM Naegle - Nucleic acids research, 2015 - academic.oup.com
… We are grateful to John Naegle for help with webpage styling, Brook Haley for help with
logo design, and Tom Ronan and Roman Sloutsky for critical reading and manuscript …
logo design, and Tom Ronan and Roman Sloutsky for critical reading and manuscript …
[HTML][HTML] Ten simple rules for effective presentation slides
KM Naegle - PLoS computational biology, 2021 - journals.plos.org
… Naegle … Citation: Naegle KM (2021) Ten simple rules for effective presentation slides.
PLoS Comput Biol 17(12): e1009554. https://doi.org/10.1371/journal.pcbi.1009554 …
PLoS Comput Biol 17(12): e1009554. https://doi.org/10.1371/journal.pcbi.1009554 …
[HTML][HTML] KSTAR: An algorithm to predict patient-specific kinase activities from phosphoproteomic data
…, BT Jordan, H Ahmed, CX Ma, KM Naegle - Nature …, 2022 - nature.com
Kinase inhibitors as targeted therapies have played an important role in improving cancer
outcomes. However, there are still considerable challenges, such as resistance, non-response…
outcomes. However, there are still considerable challenges, such as resistance, non-response…
Accounting for noise when clustering biological data
…, N Jimenez, SJ Swamidass, KM Naegle - Briefings in …, 2013 - academic.oup.com
Clustering is a powerful and commonly used technique that organizes and elucidates the
structure of biological data. Clustering data from gene expression, metabolomics and …
structure of biological data. Clustering data from gene expression, metabolomics and …